• DocumentCode
    2169795
  • Title

    Adaptive Control of an Intelligent Tank Using Fuzzy Logic

  • Author

    Yakzan, Adnan I Elberjaoui ; Khan, Atif Ali ; Hines, Evor L. ; Iliescu, Daciana

  • Author_Institution
    Sch. of Eng., Univ. of Warwick, Coventry, UK
  • fYear
    2012
  • fDate
    28-30 March 2012
  • Firstpage
    257
  • Lastpage
    262
  • Abstract
    The need for robots to work on their own is becoming highly on demand, thus artificial intelligence is a significant approach to solve real world uncertainties. In this paper, adaptive control of an intelligent tank using fuzzy logic is presented. The system shows a coherent design and fast understanding of the environment. An intelligent robot that is capable of being in a room, with no prior mapping, can understand and draw its trajectory to an intended purpose. Using a set of light detecting resistors (LDR), and IR sensors, a fuzzy controlled brain man oeuvres around obstacles and reaches a specified destination. A fuzzy controller guides the robot in searching the target and thus shooting at the target when it falls within shooting range. Moreover, another fuzzy controller helps the robot from colliding with the obstacles coming in its path. Both the controllers work simultaneously to transform an ordinary tank into an intelligent battle tank which can make decisions on its own under any environment and in any circumstances.
  • Keywords
    adaptive control; collision avoidance; fuzzy control; infrared detectors; military vehicles; IR sensors; adaptive control; artificial intelligence; coherent design; fuzzy controlled brain manoeuvres; fuzzy logic; intelligent robot; intelligent tank; light detecting resistors; obstacle collision; Fuzzy logic; Infrared sensors; Intelligent sensors; Resistors; Robot sensing systems; A/D Converter; Fuzzy Inferencing; IR; LDR;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Modelling and Simulation (UKSim), 2012 UKSim 14th International Conference on
  • Conference_Location
    Cambridge
  • Print_ISBN
    978-1-4673-1366-7
  • Type

    conf

  • DOI
    10.1109/UKSim.2012.44
  • Filename
    6205458